The Yeast Glucose Sensing Receptor is Stabilized by Interaction with Casein Kinases

Many metabolic diseases are rooted in the inability to process glucose or regulate its uptake. These processes can be explored using yeast as a model. Rgt2 is a glucose sensing receptor in yeast, and it detects glucose concentration outside the cell. This receptor is present on the plasma membrane in high glucose conditions but absent in low glucose. Western blot and a yeast two-hybrid assay were used to investigate the relationship between Rgt2 and the plasma membrane-tethered yeast casein kinases, Yck1 and Yck2. This research demonstrated that in high glucose, Rgt2 is stabilized on the plasma membrane by interaction with Yck1 and Yck2. In response to glucose, the Ycks likely phosphorylate the Rgt2 CTD between amino acids 665-696

The Process Of Obtaining And Retaining Employment Among The Vision-restricted

National estimates indicate that only a small percentage of vision-restricted individuals are employed. Identified obstacles to employment include lack of access to assistive technology, inadequate transportation, and negative attitudes of potential employers. A constructivist Grounded Theory methodology was used to gain an in-depth understanding of what people with vision-restrictions, who perceived that they are successfully employed, considered to be fundamental in the search for employment. Three themes emerged from the analysis of their responses: facing and negotiating barriers, the cyclical process of seeking and keeping employment, and settling for second best. As a person with a vision-restriction, I am uniquely situated to relate to participants and to gain insight into their employment experiences. Such knowledge may enable service providers to assist clients in implementing successful strategies, may promote attitudinal changes among employers, and may inspire job seekers not to abandon their search

GROWTH, LIPID PRODUCTION AND BIODIESEL POTENTIAL OF Chromulina freiburgensis Dofl., AN ACIDOPHILIC CHRYSOPHYTE ISOLATED FROM BERKELEY PIT LAKE

Microalgae remain a promising, but underdeveloped source of lipids for sustainable biodiesel. Some of the obstacles to cost-effective commercial-scale production have been culture contamination and expensive harvest methods. A chrysophyte isolated from Berkeley Pit Lake and identified as Chromulina freiburgensis, was found to grow rapidly in a pH 2.5 liquid medium and to amass numerous intracellular lipid bodies. This research addresses the scarcity of published knowledge on the topic of chrysophyte species as potential lipid sources for biodiesel. It investigates how growth phase, culture conditions, and harvest timing influence the quantity and composition of lipids produced by this alga. This research serves as a foundation for optimizing production of lipids that contain the most desirable fatty acid composition for biodiesel. Six experimental treatments, representing six different combinations of nutrient concentrations, were monitored and sampled during a 52-day growth period, while cellular lipid content was tracked by Nile Red fluorescence measurements. Lowering medium nitrogen concentration resulted in increased lipid production, which was further increased by lowering phosphorus concentration and supplementing with CO2. The combination of lowered nitrogen and phosphorus concentrations resulted in the highest proportion of C18:1 (50.1%) in the composition of fatty acid methyl esters from algal lipids, after approximately 22 days of stationary growth. The alga maintained its growth and favorable fatty acid composition with a modest increase in CO2. Although C. freiburgensis from Berkeley Pit Lake did not clearly demonstrate a high lipid content, its fatty acid composition is favorable for biodiesel production, and it has additional traits which may prove advantageous. Its acidic medium provides protection from culture contamination, and could potentially utilize acid mine drainage water. Fungal-assisted bioflocculation could then provide an economical means of harvest. This unique microalga is well suited for both cost-saving methods, and it has the potential to serve secondary roles in bioremediation or in CO2 removal from flue gases

Nonparametric Markovian Learning of Triggering Kernels for Mutually Exciting and Mutually Inhibiting Multivariate Hawkes Processes

In this paper, we address the problem of fitting multivariate Hawkes processes to potentially large-scale data in a setting where series of events are not only mutually-exciting but can also exhibit inhibitive patterns. We focus on nonparametric learning and propose a novel algorithm called MEMIP (Markovian Estimation of Mutually Interacting Processes) that makes use of polynomial approximation theory and self-concordant analysis in order to learn both triggering kernels and base intensities of events. Moreover, considering that N historical observations are available, the algorithm performs log-likelihood maximization in $O(N)$ operations, while the complexity of non-Markovian methods is in $O(N^{2})$. Numerical experiments on simulated data, as well as real-world data, show that our method enjoys improved prediction performance when compared to state-of-the art methods like MMEL and exponential kernels

The young binary HD 102077: Orbit, spectral type, kinematics, and moving group membership

The K-type binary star HD 102077 was proposed as a candidate member of the TW Hydrae Association (TWA) which is a young (5-15 Myr) moving group in close proximity (~50 pc) to the solar system. The aim of this work is to verify this hypothesis by different means. We first combine diffraction-limited observations from the ESO NTT 3.5m telescope in SDSS-i' and -z' passbands and ESO 3.6m telescope in H-band with literature data to obtain a new, amended orbit fit, estimate the spectral types of both components, and reanalyse the Hipparcos parallax and proper motion taking the orbital motion into account. Moreover, we use two high-resolution spectra of HD 102077 obtained with the fibre-fed optical echelle spectrograph FEROS at the MPG/ESO 2.2m telescope to determine the radial velocity and the lithium equivalent width of the system. The trajectory of HD 102077 is well constrained and we derive a total system mass of $2.6 \pm 0.8\,$ M$_{\odot}$ and a semi-major axis of $14.9 \pm 1.6\,$AU. From the i'-z' colours we infer an integrated spectral type of K2V, and individual spectral types of K0 +/- 1 and K5 +/- 1. The radial velocity corrected for the orbital motion of the system is $17.6 \pm 2\,$km/s. Even though the parallax determination from the Hipparcos data is not influenced by the orbital motion, the proper motion changes to $\mu_\alpha*\cos(\delta) = -137.84 \pm 1.26\,$ mas/yr and $\mu_\delta = -33.53 \pm 1.45 \,$mas/yr. With the resultant space motion, the probability of HD 102077 being a member of TWA is less than 1%. Furthermore, the lithium equivalent width of $200 \pm 4\,$m\AA $\,$ is consistent with an age between 30 Myr and 120 Myr and thus older than the predicted age of TWA. In conclusion, HD 102077's age, galactic space motion, and position do not fit TWA or any other young moving group

Reanalysis of the FEROS observations of HIP 11952

Aims. We reanalyze FEROS observations of the star HIP 11952 to reassess the existence of the proposed planetary system. Methods. The radial velocity of the spectra were measured by cross-correlating the observed spectrum with a synthetic template. We also analyzed a large dataset of FEROS and HARPS archival data of the calibrator HD 10700 spanning over more than five years. We compared the barycentric velocities computed by the FEROS and HARPS pipelines. Results. The barycentric correction of the FEROS-DRS pipeline was found to be inaccurate and to introduce an artificial one-year period with a semi-amplitude of 62 m/s. Thus the reanalysis of the FEROS data does not support the existence of planets around HIP 11952.Comment: 7 pages, 8 figures, 1 tabl

Online Chemical Sensor Signal Processing Using Estimation Theory: Quantification of Binary Mixtures of Organic Compounds in the Presence of Linear Baseline Drift and Outliers

Compact sensor systems for on-site monitoring of groundwater for trace organic compounds in the liquid phase are currently under development in our laboratories. Potential challenges include sensor baseline drift and the presence of outliers in the data, along with difficulties extracting the contribution of individual BTEX compound (benzene, toluene, ethylbenzene, and xylenes) from the sensor response to mixtures containing multiple chemically similar compounds. As a first step, the approach presented here permits online estimation of analyte concentrations in binary mixtures of BTEX compounds in the presence of linear baseline drift and outliers. This paper investigates a sensor signal-processing approach based on estimation theory, specifically, Kalman filter (KF), extended KF, and discrete low-pass filter. The approach permits online linear baseline drift correction, filtering of outlier points, and estimation of analyte concentration(s) in binary mixtures and single analyte samples, before the sensor response reaches steady state. Sensor signals from mixtures of BTEX compounds were analyzed because these compounds are good indicators of accidental releases of fuel and oil into groundwater. Models were first developed for the sensor response so that estimation theory can be used to obtain the sensor parameters. The baseline-drift correction technique uses KF to perform online linear extrapolation or interpolation. The presented combination of sensor signal-processing techniques was simultaneously tested using actual measured data. Unknown sensor parameters and identification of analytes in samples were obtained within a relatively short period of time (8 min or less for the present sensor system), well before the sensor response reaches equilibrium